【作者】 王晓茹； 刘亚琼； 锁然； 李荣斌； 师旭； 王焕香； 罗建华； 王颉；

【Author】 Wang Xiaoru;Liu Yaqiong;Suo Ran;Li Rongbin;Shi Xü;Wang Huanxiang;Luo Jianhua;Wang Jie;Library of Hebei Agricultural University;College of Food Science and Technology,Agricultural University of Hebei,Hebei Agricultural Products Processing Technology Innovation Center;China Great Wall Wine Co.,Ltd;Huailai Noble Winery Co.,Ltd;

【机构】 河北农业大学图书馆； 河北农业大学食品科技学院河北省农产品加工技术创新中心； 中国长城葡萄酒有限公司； 怀来县贵族庄园葡萄酒业有限公司；

【摘要】 根据世界卫生组织公布的数据,缺血性心脏病、中风、慢性阻塞性肺病、阿尔茨海默病、气管支气管和肺癌以及糖尿病为全球前6位死亡原因。本文基于经合组织2000—2013年和健康的非医学决定因素相关的7项指标(总脂肪供应X1、总热量供应X2、总蛋白质供应X3、食糖供应X4、蔬菜供应X5、水果供应X6和酒精消费X7)以及和健康状况相关的6项指标(缺血性心脏病死亡率Y1、慢性阻塞性肺病死亡率Y2、阿尔茨海默病死亡率Y3、气管、支气管和肺癌死亡率Y4、糖尿病死亡率Y5、预期寿命Y6),选取经合组织数据库预期寿命排名前十国家的数据,用和健康状况相关的6项指标分别为Y1,Y2,Y3,Y4,Y5和Y6,和健康的非医学决定因素相关的7项指标分别为X1,X2,X3,X4,X5,X6和X7,进行多元回归分析。结果表明,缺血性心脏病死亡率Y1与X5无关,与X1,X3,X4和X6呈显著正相关(P <0.01),与X2和X7呈显著负相关(P <0.01),在显著相关因子中,X1,X4,X7系数的绝对值大于1,其他相关因子的系数均较小,回归模型为Y1=270.212+1.298X1-0.147X2+0.633X3+2.122X4+0.363X6-7.011X7;慢性阻塞性肺病死亡率Y2与X7无关,与X2呈显著负相关(P<0.01),与X1,X3,X4,X5和X6呈显著正相关(P<0.01),在显著相关的因子中,相关因子的系数均较小,回归模型为Y2=59.820+0.390X1-0.054X2+0.358X3+0.441X4+0.124X5+0.131X6;阿尔茨海默病死亡率Y3与X1,X3,X4呈显著正相关(P<0.01),与X2,X5和X6呈显著负相关(P <0.01),与X7无关,显著相关因子的系数均较小,回归模型为Y3=-14.101+0.301X1-0.017X2+0.457X3+0.123X4-0.070X5-0.031X6;气管、支气管和肺癌死亡率Y4与X2,X4和X6无关,与X1和X5呈显著负相关(P<0.01),与X3和X7呈显著正相关(P <0.01),在显著相关因子中,除X7的系数大于1,其它相关因子的系数均较小,回归模型为Y4=0.870-0.052X1+0.036X3-0.022X5+1.300X7;糖尿病死亡率Y5与X2,X3和X6无关,与X1,X4和X5呈显著正相关(P <0.01),与X7呈显著负相关(P <0.01),在显著相关因子中,除X7的系数大于1,其它相关因子的系数均较小。回归模型为Y5=-18.730+0.123X1+0.236X4+0.023X5-1.621X7;预期寿命Y6与X1,X2,X3和X4无关,与X5,X6和X7(P<0.01)呈显著负相关,但相关因子的系数均较小。回归模型为Y6=82.782-0.005X5-0.013X6-0.106X7。结论:X7与Y4呈正相关,与Y1和Y5呈负相关,且系数都大于1,表明酒精消费会增加气管、支气管和肺癌死亡率,但会使缺血性心脏病和糖尿病死亡率显著下降;X1和X4与Y1呈显著正相关,且系数都大于1,表明总脂肪供应和食糖供应会增加缺血性心脏病死亡率;其它与健康相关的非医学决定因素,有的在逐步回归中被剔除,没有被剔除的系数均小于1,对Y值变化的影响较小。更多还原

【Abstract】 According to data released by the World Health Organization,ischemic heart disease,stroke,chronic obstructive pulmonary disease,Alzheimer’s disease,tracheobronchial and lung cancer and diabetes are the top 6 causes of death in the world.This paper is based on 7 Economic Cooperation Organization(OECD) indicators related to non-medical determinants of health(total fat supply X1,total calorie supply X2,total protein supply X3,sugar supply X4,vegetables supply X5,fruits supply X6 and alcohol consumption X7) and 6 indicators related to health status(ischemic heart diseases mortality Y1,chronic obstructive pulmonary diseases mortality Y2,Alzheimer’s disease mortality Y3,malignant neoplasms of trachea,bronchus,lung mortality Y4,diabetes mellitus mortality Y5,life expectancy Y6) from 2000 to 2013.Data from the top 10 countries in the OECD database were selected for multiple regression analysis using 6 indicators related to health status,including Y1,Y2,Y3,Y4,Y5 and Y6,and 7 indicators related to non-medical determinants of health,including X1,X2,X3,X4,X5,X6 and X7.The results showed that the mortality rate of ischemic heart diseases mortality Y1 had no correlation with X5,but had significant positive correlation with X1,X3,X4 and X6(P <0.01),and had significant negative correlation with X2 and X7(P <0.01).Among the significant correlation factors,the absolute values of X1,X4 and X7 coefficients were greater than 1,while the coefficients of other correlation factors were all smaller.The regression model was Y1=270.212+1.298 X1-0.147 X2+0.633 X3+2.122 X4+0.363 X6-7.011 X7.Chronic obstructive pulmonary diseases mortality Y2 had no correlation with X7,but had a significant negative correlation with X2(P <0.01),and had a significant positive correlation with X1,X3,X4,X5 and X6(P <0.01).Among the significant correlation factors,the coefficient of correlation factors was small,and the regression model was Y2=59.820+0.390 X1-0.054 X2+0.358 X3+0.441 X4+0.124 X5+0.131 X6.Alzheimer’s disease mortality rate Y3 had a significant positive correlation with X1,X3 and X4(P <0.01),and had a significant negative correlation with X2,X5 and X6(P <0.01),but had no correlation with X7.Among the significant correlation factors,the coefficient of correlation factors was small,and the regression model was Y3=-14.101+0.301 X1-0.017 X2+0.457 X3+0.123 X4-0.070 X5-0.031 X6.The malignant neoplasms of trachea,bronchus,lung Y4 had no correlation with X2,X4 and X6,but had a significant negative correlation with X1 and X5(P <0.01),and a significant positive correlation with X3 and X7(P <0.01).Among the significant correlation factors,except the coefficient of X7 was greater than 1,the coefficients of other correlation factors were all smaller,and the regression model was Y4=0.870-0.052 X1+0.036 X3-0.022 X5+1.300 X7.Life expectancy Y6 had no correlation with X1,X2,X3 and X4,but has significant negative correlation with X5,X6 and X7(P <0.01),but the coefficients of correlation factors are small.The regression model was Y6=82.782-0.005 X5-0.013 X6-0.106 X7.Conclusion:X7 was positively correlated with Y4 and negatively correlated with Y1 and Y5,and the coefficients were all greater than 1.It showed that alcohol consumption would increase the mortality rate of malignant neoplasms of trachea,bronchus,lung,but would significantly reduce the mortality rate of ischemic heart disease and Diabetes mellitus.X1 and X4 were significantly positively correlated with Y1,and the coefficients were both greater than 1,which indicating that total fat supply and sugar supply would increase the mortality rate of ischemic heart disease.Other health-related non-medical determinants,some of which were eliminated in stepwise regression,and the coefficients that were not eliminated all less than 1,which had little influence on the change of Y value.更多还原